class_docstr: Canonical metric of the Grassmann manifold.
  
  Coincides with the Frobenius metric.
docstr: Compute geodesic distance between two points.
  
  Compute the squared geodesic distance between point_a
  and point_b, as defined by the metric.
  
  This is an auxiliary private function that:
  
  - is called by the method `squared_dist` of the class
    GrassmannianCanonicalMetric,
  
  Parameters
  ----------
  point_a : array-like, shape=[..., dim]
      Point.
  point_b : array-like, shape=[..., dim]
      Point.
  
  Returns
  -------
  _ : array-like, shape=[...,]
      Geodesic distance between point_a and point_b.
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code: def _squared_dist(self, point_a, point_b):
      """Compute geodesic distance between two points.
  
      Compute the squared geodesic distance between point_a
      and point_b, as defined by the metric.
  
      This is an auxiliary private function that:
  
      - is called by the method `squared_dist` of the class
        GrassmannianCanonicalMetric,
  
      Parameters
      ----------
      point_a : array-like, shape=[..., dim]
          Point.
      point_b : array-like, shape=[..., dim]
          Point.
  
      Returns
      -------
      _ : array-like, shape=[...,]
          Geodesic distance between point_a and point_b.
      """
      return super().squared_dist(point_a, point_b)
  
imports: import geomstats.backend
  import geomstats.errors
  from geomstats.geometry.base import LevelSet
  from geomstats.geometry.general_linear import GeneralLinear
  from geomstats.geometry.matrices import Matrices, MatricesMetric
  from geomstats.geometry.symmetric_matrices import SymmetricMatrices
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 5 for calling the GrassmannianCanonicalMetric obj's underlying member method code with example usage: obj._squared_dist(point_a, point_b) and returns: super